Improved Range Resolution Research Articles

Signal Extension Method for Improved Range Resolution of Frequency-Modulated Continuous Wave Radar in Indoor Environments

Signal Extension Method for Improved Range Resolution of Frequency-Modulated Continuous Wave Radar in Indoor Environments

A Laboratory test aimed at demostrating the potential of an Interferometric Radar to estimate the Seismic Risk of damaged buildings

In the last decade, the use of interferometric Real Aperture Radar (RAR) to perform the survey of static and dynamical performance of civil structures, and estimate their vibration state and modal behaviour, for bridge monitoring, consolidated. In the case of urban buildings, due to the small amplitude of vibration of these structures, and the higher complexity of the radar survey, a few case studies have been published. Nonetheless, recent research [1] focused on the potential of measuring the frequency of vibration of a building after a seismic event to estimate the occurred damage using this non-invasive and remote sensing technique. The study here described reports the results of an experiment carried out to investigate the potential of this application through a laboratory setup. A framed metal structure, composed of bars fasten by bolts, representing a scaled reproduction of a civil building, is monitored using a portable K band (24 GHz) radar interferometer. The instrument is a prototype developed at CTTC which provides improved range resolution and displacement accuracy, with respect to the state of the art of commercial instruments. In the experiment, the structure is monitored by the radar step by step while its stiffness is decreased by loosening, in different points, the bolts constraining the structure. This procedure aim simulating an increasing damage. Simultaneously to the radar acquisitions, data from a setup of accelerometers mounted on the framed structure are also acquired. Despite the high environmental noise (radar clutter) caused by multiple reflections generated by the neighbour walls and furniture elements internal to the laboratory, the spectral analysis of the displacement samples retrieved from radar acquisitions and from the accelerometers confirm the expected behaviour. [1] Gonzalez-Drigo, R. et al., Assessment of Post-Earthquake Damaged Building with Interferometric Real Aperture Radar. Remote Sens. 2019, 11, 2830. https://doi.org/10.3390/rs11232830

Optical-pulse-based reconfigurable phase control for independent beamforming and band fusion in a dual-band phased array receiver.

This Letter proposes an optical-pulse-based reconfigurable phase control method, enabling a dual-band phased array receiver to operate in two modes: dual-band-independent operation and dual-band fusion. The method utilizes optical pulses and optical delay to compensate for phase differences across frequency bands. An electrical phase shifter is employed to compensate for phase residual in both bands. All phase operations to both bands are processed concurrently in one link, thereby maintaining inter-band phase coherence. Experimental results verify the ability of dual-band-independent beamforming and inter-band phase coherence maintaining. A four-channel dual-band (X- and Ku-band) phased array antenna (PAA) receiver is constructed to measure PAA patterns and demonstrate band fusion. The pulse compression results in all directions reveal a doubled improvement in range resolution, which shows the potential for enhancement of radar performance.

Mitigating Peak Sidelobe Levels in Pulse Compression Radar using Artificial Neural Networks

In this paper, Artificial Neural Networks (ANNs) are being considered to obtain low sidelobe pattern for binary codes and thereby to improve the performance of pulse compression radar. Pulse compression is a popular technique used for improving range resolution in the radar systems. This paper proposes a new approach for Pulse Compression using various types of ANN networks like Multi-Layer Perception (MLP), Recursive Neural Networks (RNN), Radial Basis Function (RBF) and Recurrent Radial Basis Function (RRBF) and a special class of Feed-Forward Wavelet Neural Network (WNN) with one input layer, one output layer and one hidden layer are being considered. Networks of 13-bit Barker code and extended binary Barker codes of 35, 55 and 75 length codes were used for the implementation and thereby to improve the performance of pulse compression radar. WNN-based networks using Morlet and Sigmoid activation function in hidden and output layers respectively, a special class of Artificial Neural Network is considered in this paper. The performance metrics used are Peak Sidelobe Ratio (PSLR), Integrated Sidelobe Ratio (ISLR) and Signal-to-Sidelobe Ratio (SSR). Further the performance in terms of range and Doppler resolution is also presented in this paper. Better performance in terms of sidelobe reduction can be achieved with ANNs compared to Autocorrelation Function (ACF) called as matched filter. If the sidelobe values are high there is possibility of masking weaker return signals and there by detection becomes difficult. From this paper it can be established that RRBF gives better result than other ANN networks. Further, WNN gives the best performance even compared with RRBF in terms of sidelobe reduction in pulse compression radar.

Overcoming the relative bandwidth limitations of single VCO frequency synthesizers by implementing a novel PLL architecture

Abstract Frequency-modulated continuous-wave radar systems profit from increasing the absolute bandwidths of the generated frequency chirps to improve range resolution. As the relative bandwidth of SiGe-voltage-controlled oscillators (VCOs) is limited to about 80%, increasing the center frequency fundamentally or via frequency multiplication is the most direct way to increase that absolute bandwidth. However, as some applications require penetration depth, which dramatically decreases with frequency, other solutions are necessary. Therefore, state-of-the-art concepts rely on the down-conversion of generated frequency chirps via two separately stabilized frequency sources. This article implements a novel architecture, offering relative bandwidths of >100% within a single phase-locked loop (PLL). Therefore, two VCOs at different center frequencies are fed into a down-conversion mixer, whose output is directly stabilized via that PLL with one loop filter generating both tuning voltages. Those circuit blocks can be summarized as one equivalent VCO, offering a higher relative bandwidth and a significantly more linear tuning curve. Thereby, a solution to limited relative bandwidths with high VCO gain variation of single VCO synthesizers is offered while substantially reducing the hardware and implementation effort compared to the state-of-the-art.

Sidelobes Reduction Technique for Binary Codes

Pulse compression techniques enable the radar designers to transmit long duration pulse to cater the need of high power at the transmitter and achieve the range resolution of short duration pulse at the radar receiver simultaneously. Due to easy generation and processing, binary codes are widely used as pulse compression codes in radars, sonars and spread-spectrum communication systems. But binary codes have high unwanted pulse compression sidelobes at the output of pulse compression receivers. In this paper, optimum binary codes reported in the literatures are overlaid on Discrete frequency sequences to reduce unwanted peaks sidelobes of optimum binary codes. The proposed approach not only reduced peak sidelobes of optimum binary codes but also increased the pulse compression ratio. In this paper, optimum discrete frequency sequences for overlaying with binary codes are optimized using the Modified Simulated Annealing Algorithm (MSAA). A Discrete Frequency Coded binary signal has a complex signal structure which will be difficult to detect and analyze by enemy Electronics Support Measures (ESM). In this paper, a unified adaptive radar model is also proposed to cater the needs of today's radar signal design requirements. The proposed model will help to improve range resolution, the detection capability of radar, reduce the peak sidelobes significantly, and also improve the ESM capability of radar systems.

Photonic generation of Barker encoded dual-nonlinear frequency modulated RADAR waveforms

Photonics enables the development of versatile waveform generators with carrier frequency tunability and broad bandwidths, allowing for high-range resolution for modern radar systems. Linear frequency-modulated waveforms are widely employed in various radar applications due to their large time-bandwidth products but are limited in functionality due to high sidelobe levels, resulting in a poor signal-to-noise ratio (SNR). On the other hand, non-linear frequency-modulated waveforms (NLFM) have a faster sweep rate at the edges than at the center, resulting in high SNRs, which can be boosted further through encoding techniques. A photonic approach for generating Barker-encoded dual-NLFM waveforms through a dual-drive Mach Zehnder modulator is proposed with improved range resolution, pulse compression ratio, and peak-to-sidelobe ratio. A theoretical analysis is performed, which is then modeled, and experimentally confirmed. Barker-encoded dual-NLFM waveforms are generated at 6 GHz with 500 MHz chirp bandwidth showing a maximum range resolution of 19.89 cm with PCR of 9803.

4D radar simulator for human activity recognition

AbstractMillimetre‐wave radar has been widely used in health monitoring and human activity recognition owing to its improved range resolution and operation in a variety of environmental conditions. With the MIMO antenna array, 4D radar is increasingly employed in autonomous driving, while its application in assisted living is recent and therefore the value added compared to the increase in signal processing and hardware requirements is still an open question. A model for 4D Time‐division multiplexing (TDM) multiple‐input‐multiple‐output (MIMO) frequency‐modulated Continuous wave radar is established using the human activities from the HDM05 motion capture dataset. The simulator produces an end‐to‐end simulation, including four human motions (jumping Jack, kick, punch, and walk), signal time of flight, noise, MIMO signal processing, and classification. Different pre‐processing and point cloud‐based methods are compared to obtain an average classification accuracy of 90% with PointNet. This study simulates a specific 4D TDM MIMO radar configuration to benchmark signal pre‐processing algorithms, which can also assist other researchers to generate range‐Doppler‐time (range‐Doppler time) point cloud data sets for human activities testing different radar configurations, array configurations, and activities saving valuable time in human resources and hardware development before prototyping to assess expected performances.

Multitarget Detection and Tracking by Mitigating Spot Jammer Attack in 77-GHz mm-Wave Radars: An Experimental Evaluation

Small form factor radar sensors at millimeter wavelengths find numerous applications in the industrial and automotive sectors. These radar sensors provide improved range resolution, good angular resolution, and enhanced Doppler resolution for short range and ultrashort ranges. However, it is challenging to detect and track the targets accurately when a radar is interfered by another radar. This article proposes an experimental evaluation of a 77-GHz IWR1642 radar sensor in the presence of a second 77-GHz AWR1642 radar sensor acting as a spot jammer. A real-time experiment is carried out by considering five different targets of various cross sections, such as a car, a larger size motorcycle, a smaller size motorcycle, a cyclist, and a pedestrian. The collected real-time data are processed by four different constant false alarm rate detectors, cell averaging (CA)-CFAR, ordered statistics (OS)-CFAR, greatest of CA (GOCA)-CFAR, and smallest of CA (SOCA)-CFAR. Following that, data from these detectors are fed into two different clustering algorithms (density-based spatial clustering of applications with noise (DBSCAN) and K-means), followed by the extended Kalman filter (EKF)-based tracker with global nearest neighbor (GNN) data association, which provide tracks of various targets with and without the presence of a jammer. Furthermore, four different metrics [tracks reported (TR), track segments (TSs), false tracks (FTs), and track loss (TL)] are used to evaluate the performance of various tracks generated for two clustering algorithms with four detection schemes. The experimental results show that the DBSCAN clustering algorithm outperforms the K-means clustering algorithm for many cases.

Loading the tumor with 31P, 63Cu and 89Y provides an in vivo prompt gamma-based range verification for therapeutic protons

Introduction: The main rationale for using protons in cancer treatment is based on the highly conformal dose distribution and normal tissue spearing compared to conventional radiotherapy. The main limit of proton therapy is the particle range uncertainty due to patient setup, dose calculation and imaging. To account for this, a safety margin is added to the tumor to ensure the prescribed dose to the target. Reducing range uncertainties would result in the reduction of irradiation volume and would allow full exploitation of the proton therapy benefits. In this work, we presented a feasibility study for a strategy to achieve in vivo proton range verification based on prompt gammas (PG). This approach relies on the detection of signature prompt gammas, generated by the interaction of primary protons with a non-radioactive element, that is selectively loaded into a tumor with a drug carrier. The number of characteristic gammas is directly related to the proton range, and its measurement provides an estimate of the position at which the primary beam stops with respect to the tumor location.Method: We identified the criteria for selecting potential candidate materials and combined them with TALYS predictions to make the selection. We carried out an experimental campaign to characterize the PG spectra generated by the chosen materials when irradiated with therapeutic protons and compared them with TOPAS Monte Carlo toolkit predictions.Results: We identified 31-Phosphorous, 63-Copper and 89-Yttrium as potential candidates for this application based on TALYS calculations. The experimental data confirmed that all candidates emit signature prompt gammas different from water (here used as a proxy for normal tissue), and that the gamma yield is directly proportional to the element concentration in the solution. Four specific gamma lines were detected for both 31P (1.14, 1.26, 1.78, and 2.23 MeV) and 63Cu (0.96, 1.17, 1.24, 1.326 MeV), while only one for 89Y (1.06 MeV). The simulations indicate that the count of characteristic gammas is directly proportional to the proton range, reaching in some cases a saturation value around the tumor’s far edge. The results also indicate that to achieve a range accuracy below the current value of 2–3 mm, the uncertainty on the prompt gammas count has to be below 5% for 31-Phosphorous and 63-Copper, or 10% for 89-Yttrium.Discussion: We demonstrated that loading the tumor with a label element prior to proton treatment generates signature gammas that can be used to verify the beam range in vivo, reaching a potential range accuracy below the current limitations. This approach can be either used stand-alone or combined with other existing methodologies to further improve range resolution.

Range Resolution Improvement Using Cross-Track Interferometry for FMCW Radar

Range Resolution Improvement Using Cross-Track Interferometry for FMCW Radar

Method for Improving Range Resolution of Indoor FMCW Radar Systems Using DNN.

Various studies on object detection are being conducted, and in this regard, research on frequency-modulated continuous wave (FMCW) RADAR is being actively conducted. FMCW RADAR requires high-distance resolution to accurately detect objects. However, if the distance resolution is high, a high-modulation bandwidth is required, which has a prohibitively high cost. To address this issue, we propose a two-step algorithm to detect the location of an object through DNN using many low-cost FMCW RADARs. The algorithm first infers the sector by measuring the distance to the object for each FMCW RADAR and then measures the position through the grid according to the inferred sector. This improves the distance resolution beyond the modulation bandwidth. Additionally, to detect multiple targets, we propose a Gaussian filter. Multiple targets are detected through an ordered-statistic constant false-alarm rate (OS-CFAR), and there is an 11% probability that multiple targets cannot be detected. In the lattice structure proposed in this paper, the performance of the proposed algorithm compared to those in existing works was confirmed with respect to the cost function. The difference in performance versus complexity was also confirmed when the proposed algorithm had the same complexity and the same performance, and it was confirmed that there was a performance improvement of up to five-fold compared to those in previous papers. In addition, multi-target detection was shown in this paper. Through MATLAB simulation and actual measurement on a single target, RMSEs were 0.3542 and 0.41002 m, respectively, and through MATLAB simulation and actual measurement on multiple targets, RMSEs were confirmed to be 0.548265 and 0.762542 m, respectively. Through this, it was confirmed that this algorithm works in real RADAR.

Range Resolution Improvement of GNSS-Based Passive Radar via Incremental Wiener Filter

Range Resolution Improvement of GNSS-Based Passive Radar via Incremental Wiener Filter

3-D electromagnetic-model-based absolute attitude estimation using a deep neural network

ABSTRACT With the improvement of range resolution, wideband radars can achieve not only the range and velocity but also signature information of the target, such as the target RCS and the distribution of the scattering centres. Since radar target signature is closely related to target’s geometric structure and attitude, it is possible to estimate attitude from wideband radar echoes. To this end, we propose a novel end-to-end Radar Target Attitude Estimation Network (RTAENet) to estimate the absolute attitude of the radar target. A difficulty for training the network is that a large dataset with ground truth is required. To solve this issue, we introduce the three-dimensional (3-D) electromagnetic model to generate training samples. Since the RTAENet requires very little feature engineering by hand and can take advantage of increases in the amount of available data, it achieves high accuracy for attitude estimation. Experiments using both data predicted by a high-frequency electromagnetic code and data measured in an anechoic chamber demonstrate the feasibility of the proposed method.

Signal Expansion Method in Indoor FMCW Radar Systems for Improving Range Resolution.

As various unmanned autonomous driving technologies such as autonomous vehicles and autonomous driving drones are being developed, research on FMCW radar, a sensor related to these technologies, is actively being conducted. The range resolution, which is a parameter for accurately detecting an object in the FMCW radar system, depends on the modulation bandwidth. Expensive radars have a large modulation bandwidth, use the band above 77 GHz, and are mainly used as in-vehicle radar sensors. However, these high-performance radars have the disadvantage of being expensive and burdensome for use in areas that require precise sensors, such as indoor environment motion detection and autonomous drones. In this paper, the range resolution is improved beyond the limited modulation bandwidth by extending the beat frequency signal in the time domain through the proposed Adaptive Mirror Padding and Phase Correction Padding. The proposed algorithm has similar performance in the existing Zero Padding, Mirror Padding, and Range RMSE, but improved results were confirmed through the indicating the size of the side lobe compared to the main lobe and the accurate detection rate of the OS CFAR. In the case of , it was confirmed that with single targets, Adaptive Mirror Padding was improved by about 3 times and Phase Correct Padding was improved by about 6 times compared to the existing algorithm. The results of the OS CFAR were divided into single targets and multiple targets to confirm the performance. In single targets, Adaptive Mirror Padding improved by about 10% and Phase Correct Padding by about 20% compared to the existing algorithm. In multiple targets, Phase Correct Padding improved by about 20% compared to the existing algorithm. The proposed algorithm was verified through the MATLAB Tool and the actual FMCW radar. As the results were similar in the two experimental environments, it was verified that the algorithm works in real radar as well.

Binning-based local-threshold filtering for enhancement of underwater 3D gated range-intensity correlation imaging.

3D gated range-intensity correlation imaging (GRICI) can reconstruct a 3D scene with high range resolution in real time. However, in the applications of underwater range-gated imaging, targets with low reflectivity or at a far distance typically have a low signal-to-noise ratio (SNR), especially in turbid water. Usually, a global threshold is set to suppress noise in gated images, which easily results in data holes in the degraded depth map reconstructed by 3D GRICI. To solve the problem, we have proposed a binning-based local-threshold filtering (BLF) algorithm to fill depth data holes. Firstly, raw gated images are added to obtain a sum image, and global threshold filtering and pixel binning for the sum image are used to obtain a reference image. Secondly, hole pixels can be registered according to the reference image. Finally, a smaller local threshold is reset for the hole pixels, and then a repaired depth map is given by 3D GRICI. The experimental results have shown that the proposed method can effectively fill depth data holes and the peak signal-to-noise ratio of the repaired depth map is increased from 10.23 dB to 22.45 dB by suppressing water noise with the improved range resolution from 6.25 mm to 4.12 mm. In addition, the 3D depth of viewing is enlarged, and the limit detection distance is increased by 21% in experiment. The research can promote the practical applications of 3D GRICI.

Space-Time Coding Technique for Coherent Frequency Diverse Array

Coherent frequency diverse array (FDA) radar is able to cover all directions with a stable gain by transmitting a single frequency-shifted waveform. However, it is revealed in this work that the range resolution scales linearly with the number of elements, which is limited by the fixed element number. By leveraging the relationship between the beam direction and the signal frequency, we link the sub-bands of the emitted signal to angular sectors. Based on the fact, a novel transmit diversity technique, referred to as two-dimensional (2-D) space-time coding (STC), is proposed to improve the range resolution. For a specific observation direction, the frequency band of each pulse is shifted by STC to synthesize a full bandwidth after the pulse accumulation. Furthermore, the piecewise LFM (linear frequency modulation) waveform design can be combined with the STC technique to synthesize the transmit beampattern flexibly without range resolution degradation for each pulse. Compared with the state-of-the-art technologies, the proposed STC technique has superiorities in range resolution improvement, ultra-low range sidelobe level, interference suppression, and beampattern design capability. In addition, multi-dimensional ambiguity functions are derived to assess the performance in range-angle-Doppler domain, including the range and angle resolutions, the sidelobe level (SLL) and the angular coverage. To satisfy practical demands, the general receive processing procedures are also designed. The proposed method and corresponding theoretical analysis are verified by extensive numerical results.

Receive Filter Design Considering a Complete Second Order Characterization

In active sensing applications, the design of sequences that improve the estimation and detection of objects in a medium is of fundamental interest. Two approaches are commonly employed to process the received data and improve range resolution as well as target detection. They involve the use of either a matched or a mismatched filter. Traditionally, the synthesis of these filters is based upon criteria that consider a partial second order characterization of the processed signals, being the only design parameter the minimization of the correlation sidelobes. This approach has proven to be adequate when strictly linear systems are used to model the scenarios under analysis. Here, we extend the synthesis approach of the receive filter when the profile to be estimated can be modeled by a widely linear system, whose output is affected with additive noise. The computation of the receive filter coefficients is based on the minimization of the peak sidelobe level (PSL) due to the correlation and complementary correlation of the processed signals. The resultant optimization problem is addressed by making use of the minimax algorithm, which can be implemented efficiently in a computer. Numerical results show that it is possible to jointly minimize the second order moments of the receive filter, however, for some scenarios a bound is reached where it is not possible to further decrease the magnitude of the correlation and complementary correlation of the filter with the probing sequence.

DVB-T Receiver Independent of Channel Allocation, With Frequency Offset Compensation for Improving Resolution in Low Cost Passive Radar

In this article, a commercial low cost solution for increasing DVB-T based passive radar (also referred to as passive coherent location) robustness with respect to channel allocation and range resolution, is designed. IDEPAR demonstrator is updated to include a new recording system in charge of DVB-T channels reallocation. The use of commercial hardware introduces frequency mismatching between acquired channels that compromises system operation. To face channel frequency alignment, fulfilling the requirements imposed by the high Doppler resolution typical of passive radars, a novel compensation algorithm is proposed, based on the minimization of signal dispersion in the Cross-Ambiguity Function domain. The well-known cyclic prefix van de Beek method is used as reference. Results show an increase in target signal to interference ratio and detection performances, as well as a reduction of clutter dispersion when the novel proposed algorithm is applied. The low cost solution is also compared to a high performance one capable of acquiring a wide bandwidth of sparse DVB-T channels, and performing channel reallocation by digital signal processing. Results show that both systems reached similar performances in terms of range resolution and SNR improvement.

An Image Formation Algorithm for Bistatic SAR Using GNSS Signal With Improved Range Resolution

Passive synthetic aperture radar (SAR) using Global Navigation Satellite System (GNSS) signals as the illuminators of opportunity has a relative coarse range resolution due to the narrow bandwidth of the navigation signals and the bi-static acquisition geometry, limiting its application for high-resolution requirement. In this paper, an image formation algorithm for range resolution improvement is investigated. A modified second order differentiation based method is applied on the range compressed signal of reference channel and surveillance channel, improving range resolution and keeping side-lobes at a lower level simultaneously, and the phase of processed signal is preserved by phase multiplication compensation for the following azimuth compression processing. To validate the effectiveness and benefits of the proposed algorithm in terms of range resolution and targets side-lobes, point targets simulation under different situations and real field experiment with strong scatters are conducted and discussed. Compared with the traditional GNSS-based passive SAR imaging algorithm, the results of the proposed method show that the imaging performance can be improved for better range resolution and lower side-lobes, benefitting for better distinguishing nearby targets and recognizing weak targets.